suppressPackageStartupMessages(library(tidyverse))
library(gapminder)
Saving Graphs to File
- Don’t use the mouse
- Use
ggsave for ggplot
- Practice by saving the following plot to file:
ggplot(mtcars, aes(hp, wt)) +
geom_point()
ggsave(FILENAME_HERE, PLOT_OBJECT_HERE)
- Base R way: print plots “to screen”, sandwiched between
pdf()/jpeg()/png()… and dev.off().
- Vector vs. raster: Images are stored on your computer as either vector or raster.
Scales; Colour
Scale functions in ggplot2 take the form scale_[aesthetic]_[mapping]().
Let’s first focus on the following plot:
p_scales <- ggplot(gapminder, aes(gdpPercap, lifeExp)) +
geom_point(aes(colour=pop), alpha=0.2)
p_scales +
scale_x_log10() +
scale_colour_continuous(trans="log10")

- Change the y-axis tick mark spacing to 10; change the colour spacing to include all powers of 10.
p_scales +
scale_x_log10() +
scale_colour_continuous(
trans = "log10",
breaks = FILL_IN_BREAKS
) +
FILL_IN_SCALE_FUNCTION(breaks=FILL_IN_BREAKS)
- Specify
scales::*_format in the labels argument of a scale function to do the following:
- Change the x-axis labels to dollar format (use
scales::dollar_format())
- Change the colour labels to comma format (use
scales::comma_format())
library(scales)
Attaching package: ‘scales’
The following object is masked from ‘package:purrr’:
discard
The following object is masked from ‘package:readr’:
col_factor
p_scales +
scale_x_log10(labels=dollar_format()) +
scale_colour_continuous(
trans = "log10",
breaks = 10^(1:10),
labels = comma_format()
) +
scale_y_continuous(breaks=10*(1:10))

- Use
RColorBrewer to change the colour scheme.
- Notice the three different types of scales: sequential, diverging, and continuous.
## All palettes the come with RColorBrewer:
RColorBrewer::display.brewer.all()

p_scales +
scale_x_log10(labels=dollar_format()) +
scale_color_distiller(
trans = "log10",
breaks = 10^(1:10),
labels = comma_format(),
palette = "Greens"
) +
scale_y_continuous(breaks=10*(1:10))

- Use
viridis to change the colour to a colour-blind friendly scheme
- Hint: add
scale_colour_viridis_c (c stands for continuous; d discrete).
- You can choose a palette with
option.
p_scales +
scale_x_log10(labels=dollar_format()) +
scale_colour_viridis_c(
trans = "log10",
breaks = 10^(1:10),
labels = comma_format()
) +
scale_y_continuous(breaks=10*(1:10))

Theming
Changing the look of a graphic can be achieved through the theme() layer.
There are “complete themes” that come with ggplot2, my favourite being theme_bw (I’ve grown tired of the default gray background, so theme_bw is refreshing).
- Change the theme of the following plot to
theme_bw():
ggplot(iris, aes(Sepal.Width, Sepal.Length)) +
facet_wrap(~ Species) +
geom_point() +
labs(x = "Sepal Width",
y = "Sepal Length",
title = "Sepal sizes of three plant species") +
theme_bw()

- Then, change font size of axis labels, and the strip background colour. Others?

Plotly
Consider the following plot:
(p <- gapminder %>%
filter(continent != "Oceania") %>%
ggplot(aes(gdpPercap, lifeExp)) +
geom_point(aes(colour=pop), alpha=0.2) +
scale_x_log10(labels=dollar_format()) +
scale_colour_distiller(
trans = "log10",
breaks = 10^(1:10),
labels = comma_format(),
palette = "Greens"
) +
facet_wrap(~ continent) +
scale_y_continuous(breaks=10*(1:10)) +
theme_bw())

- Convert it to a
plotly object by applying the ggplotly() function:
library(plotly)
Loading required package: ggplot2
Attaching package: ‘plotly’
The following object is masked from ‘package:ggplot2’:
last_plot
The following object is masked from ‘package:stats’:
filter
The following object is masked from ‘package:graphics’:
layout
ggplotly (p)
- You can save a plotly graph locally as an html file. Try saving the above:
- NOTE: plotly graphs don’t seem to show up in Rmd notebooks, but they do with Rmd documents.
p %>%
ggplotly() %>%
htmlwidgets::saveWidget("LOCATION_GOES_HERE")
- Run this code to see the json format underneath:
p %>%
ggplotly() %>%
plotly_json()
Error: Package `listviewer` required for `plotly_json`.
Please install and try again.
- Check out code to make a plotly object from scratch using
plot_ly() – scatterplot of gdpPercap vs lifeExp.
plot_ly(gapminder,
x = ~gdpPercap,
y = ~lifeExp,
type = "scatter",
mode = "markers",
opacity = 0.2) %>%
layout(xaxis = list(type = "log"))
- Add population to form a z-axis for a 3D plot:
plot_ly(gapminder,
x = ~gdpPercap,
y = ~lifeExp,
z = ~pop,
type = "scatter3d",
mode = "markers",
opacity = 0.2)
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ZXMoU2VwYWwuV2lkdGgsIFNlcGFsLkxlbmd0aCkpICsKICAgICBmYWNldF93cmFwKH4gU3BlY2llcykgKwogICAgIGdlb21fcG9pbnQoKSArCiAgICAgbGFicyh4ID0gIlNlcGFsIFdpZHRoIiwKICAgICAgICAgIHkgPSAiU2VwYWwgTGVuZ3RoIiwKICAgICAgICAgIHRpdGxlID0gIlNlcGFsIHNpemVzIG9mIHRocmVlIHBsYW50IHNwZWNpZXMiKSArCiAgICB0aGVtZV9idygpICsKICAgIHRoZW1lKGF4aXMudGV4dCA9IGVsZW1lbnRfdGV4dChzaXplID0gMTYpLAogICAgICAgICAgc3RyaXAuYmFja2dyb3VuZCA9IGVsZW1lbnRfcmVjdChmaWxsID0gIm9yYW5nZSIpLCAKICAgICAgICAgIHBhbmVsLmJhY2tncm91bmQgPSBlbGVtZW50X3JlY3QoZmlsbCA9ICJibHVlIikpCmBgYAoKCiMgUGxvdGx5CgpDb25zaWRlciB0aGUgZm9sbG93aW5nIHBsb3Q6CgpgYGB7cn0KKHAgPC0gZ2FwbWluZGVyICU+JSAKICAgICBmaWx0ZXIoY29udGluZW50ICE9ICJPY2VhbmlhIikgJT4lIAogICAgIGdncGxvdChhZXMoZ2RwUGVyY2FwLCBsaWZlRXhwKSkgKwogICAgIGdlb21fcG9pbnQoYWVzKGNvbG91cj1wb3ApLCBhbHBoYT0wLjIpICsKICAgICBzY2FsZV94X2xvZzEwKGxhYmVscz1kb2xsYXJfZm9ybWF0KCkpICsKICAgICBzY2FsZV9jb2xvdXJfZGlzdGlsbGVyKAogICAgICAgICB0cmFucyAgID0gImxvZzEwIiwKICAgICAgICAgYnJlYWtzICA9IDEwXigxOjEwKSwKICAgICAgICAgbGFiZWxzICA9IGNvbW1hX2Zvcm1hdCgpLAogICAgICAgICBwYWxldHRlID0gIkdyZWVucyIKICAgICApICsKICAgICBmYWNldF93cmFwKH4gY29udGluZW50KSArCiAgICAgc2NhbGVfeV9jb250aW51b3VzKGJyZWFrcz0xMCooMToxMCkpICsKICAgICB0aGVtZV9idygpKQpgYGAKCjEuIENvbnZlcnQgaXQgdG8gYSBgcGxvdGx5YCBvYmplY3QgYnkgYXBwbHlpbmcgdGhlIGBnZ3Bsb3RseSgpYCBmdW5jdGlvbjoKCmBgYHtyfQpsaWJyYXJ5KHBsb3RseSkKZ2dwbG90bHkgKHApCmBgYAoKMi4gWW91IGNhbiBzYXZlIGEgcGxvdGx5IGdyYXBoIGxvY2FsbHkgYXMgYW4gaHRtbCBmaWxlLiBUcnkgc2F2aW5nIHRoZSBhYm92ZToKICAgIC0gTk9URTogcGxvdGx5IGdyYXBocyBkb24ndCBzZWVtIHRvIHNob3cgdXAgaW4gUm1kIF9ub3RlYm9va3NfLCBidXQgdGhleSBkbyB3aXRoIFJtZCBfZG9jdW1lbnRzXy4KCmBgYHtyfQpwICU+JSAKICAgIGdncGxvdGx5KCkgJT4lIAogICAgaHRtbHdpZGdldHM6OnNhdmVXaWRnZXQoIkxPQ0FUSU9OX0dPRVNfSEVSRSIpCmBgYAoKCjMuIFJ1biB0aGlzIGNvZGUgdG8gc2VlIHRoZSBqc29uIGZvcm1hdCB1bmRlcm5lYXRoOgoKYGBge3J9CnAgJT4lIAogICAgZ2dwbG90bHkoKSAlPiUgCiAgICBwbG90bHlfanNvbigpCmBgYAoKCjQuIENoZWNrIG91dCBjb2RlIHRvIG1ha2UgYSBwbG90bHkgb2JqZWN0IGZyb20gc2NyYXRjaCB1c2luZyBgcGxvdF9seSgpYCAtLSBzY2F0dGVycGxvdCBvZiBnZHBQZXJjYXAgdnMgbGlmZUV4cC4KICAgIC0gQ2hlY2sgb3V0IHRoZSBbY2hlYXQgc2hlZXRdKGh0dHBzOi8vaW1hZ2VzLnBsb3QubHkvcGxvdGx5LWRvY3VtZW50YXRpb24vaW1hZ2VzL3JfY2hlYXRfc2hlZXQucGRmKS4KCmBgYHtyfQpwbG90X2x5KGdhcG1pbmRlciwgCiAgICAgICAgeCA9IH5nZHBQZXJjYXAsIAogICAgICAgIHkgPSB+bGlmZUV4cCwgCiAgICAgICAgdHlwZSA9ICJzY2F0dGVyIiwKICAgICAgICBtb2RlID0gIm1hcmtlcnMiLAogICAgICAgIG9wYWNpdHkgPSAwLjIpICU+JSAKICAgIGxheW91dCh4YXhpcyA9IGxpc3QodHlwZSA9ICJsb2ciKSkKYGBgCgo1LiBBZGQgcG9wdWxhdGlvbiB0byBmb3JtIGEgei1heGlzIGZvciBhIDNEIHBsb3Q6CgpgYGB7cn0KcGxvdF9seShnYXBtaW5kZXIsIAogICAgICAgIHggPSB+Z2RwUGVyY2FwLCAKICAgICAgICB5ID0gfmxpZmVFeHAsIAogICAgICAgIHogPSB+cG9wLAogICAgICAgIHR5cGUgPSAic2NhdHRlcjNkIiwKICAgICAgICBtb2RlID0gIm1hcmtlcnMiLAogICAgICAgIG9wYWNpdHkgPSAwLjIpCmBgYAoKCg==